WFP PRISM Frontend

This project is the front-end interface for the World Food Programme's PRISM project. It displays data, forecasts, and impact projections on a configurable map interface.

Functionalities

The new PRISM frontend is built as a static website to minimize cross dependencies and simplify deployments as much as possible. Currently, PRISM frontend provides the ability to:

Load administrative boundaries as GeoJSON (src/config/admin_boundaries.json)
Load baseline data as JSON, and link it to administrative boundaries
Display WMS layers from Geoserver or Open Data Cube endpoints, with date selection capabilities
Display CSV tables in a left side panel

Configuration

The configuration is split into four files that you can find in src/config:

1. prism.json
1. layers.json
1. tables.json
1. baseline.ts

prism.json

This is the primary configuration file. You can define:

The server endpoints
Map settings (starting point, zoom)
Categories

The default categories are baseline, climate, impact and tables. For each categories, you can define sub categories as "subcategorie_name": [layers], a list of layers from layers.json.

layers.json

There are 3 main types of layers:

raster

These layers are simply processed as raster images from a server.

"pasture_anomaly": {
    "title": "Pasture anomaly",
    "server_type": "wms",
    "server_layer": "ModisAnomaly",
    "server_uri": "https://mongolia.sibelius-datacube.org:5000/wms?layers=ModisAnomaly",
    "has_date": true,
    "date_interval": "days",
    "opacity": 0.3,
    "legend_text": "Converts  NDVI to pasture (kg/ha) values and divides the current period by the long term average to calculate pasture anomaly.",
    "legend": [
        { "value": "12000", "color": "#ff0000" },
        { "value": "14000", "color": "#ff5900" },
        { "value": "16000", "color": "#ff8400" },
        { "value": "18000", "color": "#ffce63" },
        { "value": "19000", "color": "#ffdd94" },
        { "value": "20000", "color": "#ffffbf" },
        { "value": "21000", "color": "#dee09f" },
        { "value": "22000", "color": "#bbbf7c" },
        { "value": "24000", "color": "#9da360" },
        { "value": "26000", "color": "#7e8745" },
        { "value": "28000", "color": "#5b6e00" }
    ]
}

baseline

The layers are obtained by matching data from the data field with the administrative boundaries. The data field should point to a dataset defined in baseline.ts

"population_below_poverty": {
    "title": "Population below national poverty line (%)",	    "title": "Poverty Headcount",
    "server_type": "wms",	    "type": "json",
    "server_uri": "https://mng-wfp.ovio.org:8443/geoserver/prism/wms?service=WMS&layers=poverty_HC",	    "data": "nsoPoverty",
    "admin_code": "CODE1",
    "has_date": false,	    "has_date": false,
    "opacity": 0.3,	    "opacity": 0.3,
    "legend_text": "Source: Susenas"	    "legend": [
      { "value": "25", "color": "#fef0d9" },
      { "value": "30", "color": "#fdcc8a" },
      { "value": "35", "color": "#fc8d59" },
      { "value": "40", "color": "#e34a33" },
      { "value": "45", "color": "#b30000" }
    ],
    "legend_text": "The poverty headcount is the share of the population whose consumption / expenditure is below the poverty line by Aimag. Year: 2018. Source: National Statistics Office"
}

impact

"herd_pasture_impact": {
    "title": "Number of herder households exposed to severe pasture anomaly",
    "hazard_layer": "pasture_anomaly",
    "baseline_layer": "nsoHerders",
    "threshold": " <= 25000",
    "opacity": 0.3,
    "legend_text": "Number of herder households within ADMIN2 in an area where the median pasture anomaly is <= -50%",
    "legend": [
      { "value": "25", "color": "#ffeda0”" },
      { "value": "30", "color": "#feb24c”" },
      { "value": "35", "color": "#f03b20”" }
    ]
}

baseline.ts

This file is used to pre-load datasets and make sure that they are formatted properly. Thanks to TypeScript, this is limitting the potential for mismatch and failed loads.

Technical - Packages/Dependencies

This project was bootstrapped with Create React App, using the Redux and Redux Toolkit template with TypeScript.

Styling & UI Library Use Material UI. Note that to use the styles API you can import @material-ui/core/styles.
Routing Uses React Router.
Mapping Uses MapBox. To use the app, you will need to create a token and add it as REACT_APP_MAPBOX_TOKEN in a .env file at the root folder.
Monitoring Uses Sentry.io. To send monitoring info to Sentry, simply set the Sentry url by adding it as REACT_SENTRY_URL in a .env file at the root folder.
State Management Uses Redux
Testing Uses Jest with Enzyme

Available Scripts

In the project directory, you can run:

`yarn start`

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

`yarn test`

Launches the test runner in the interactive watch mode.
See the section about running tests for more information.

`yarn build`

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes.
Your app is ready to be deployed!

See the section about deployment for more information.

`yarn lint`

Runs eslint for all the source files. We use a custom Eslint configuration in ./eslintrc along with prettier (configured with ./.prettierrc) to enforce consistency and code quality. If you would like eslint to try to automatically "fix" files if it can, run yarn lint --fix.

Committing Code

By default, a pre-commit hook is defined to run linting tasks on all staged code before allowing a commit. This occurs using the lint-staged package, and can be configured in ./package.json#lint-staged. The precommit task can be run manually using yarn precommit.

valpesendorfer / prism-frontend